Results 41 to 50 of about 917,002 (254)
Multisensory Causal Inference in the Brain [PDF]
At any given moment, our brain processes multiple inputs from its different sensory modalities (vision, hearing, touch, etc.). In deciphering this array of sensory information, the brain has to solve two problems: (1) which of the inputs originate from the same object and should be integrated and (2) for the sensations originating from the same object,
Kayser, Christoph, Shams, L.
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Implementing Causal Inference in Ecology Through the Structural Causal Model (SCM) Framework
Ecologists are often interested in understanding causal relationships from ecological data. However, developed methods for causal inference, particularly for observational-based studies are often not taught or applied in ecology.
Arif, Suchinta
core
ABSTRACT Background Children with sickle cell anemia (SCA) in low‐income settings are at risk of severe malnutrition, but optimal nutritional management has not been established. We evaluated an intensified ready‐to‐use therapeutic food (RUTF) regimen in children with persistent severe malnutrition after initial treatment and assessed whether early ...
Safiya Gambo +9 more
wiley +1 more source
Interventional Approach for Path-Specific Effects
Standard causal mediation analysis decomposes the total effect into a direct effect and an indirect effect in settings with only one single mediator.
Lin Sheng-Hsuan, VanderWeele Tyler
doaj +1 more source
Causal Inference with Deep Causal Graphs
Supplementary material can be found in https://github.com/aparafita/dcg ...
Álvaro Parafita, Jordi Vitrià
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ABSTRACT Background Survivors of pediatric brain tumors (PBTs) can experience long‐term social difficulties, impacting quality of life. Beyond medical and environmental factors, family psychosocial risk may play a role in social outcomes by shaping the caregiving environment and may provide intervention options.
Renske H. Houben +4 more
wiley +1 more source
Principal Stratification in Causal Inference [PDF]
Summary. Many scientific problems require that treatment comparisons be adjusted for posttreatment variables, but the estimands underlying standard methods are not causal effects. To address this deficiency, we propose a general framework for comparing treatments adjusting for posttreatment variables that yields principal effects based on principal ...
Frangakis, Constantine E. +1 more
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A Kernel-Based Metric for Balance Assessment
An important goal in causal inference is to achieve balance in the covariates among the treatment groups. In this article, we introduce the concept of distributional balance preserving which requires the distribution of the covariates to be the same in ...
Zhu Yeying +2 more
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ABSTRACT Background Allogeneic hematopoietic stem cell transplantation (alloHSCT) is an essential therapy for several malignant and nonmalignant diseases, but relapse and graft loss remain the principal threats to its success. Routine monitoring of chimerism and minimal residual disease (MRD) enables early detection of imminent recurrence and guides ...
Carmen Junk +10 more
wiley +1 more source
Learning Heterogeneity in Causal Inference Using Sufficient Dimension Reduction
Often the research interest in causal inference is on the regression causal effect, which is the mean difference in the potential outcomes conditional on the covariates. In this paper, we use sufficient dimension reduction to estimate a lower dimensional
Luo Wei, Wu Wenbo, Zhu Yeying
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